Abstract: Disclosed herein are embodiments of systems, methods, and products comprise a processor, which provides runtime enforcement of data flow integrity. The processor accesses the application binary file from the disk to execute an application and translates the application binary into intermediate representation. The processor applies the logic of data flow integrity controls to the intermediate representation. Specifically, the processor identifies the vulnerable code in the intermediate representation. The processor applies data flow integrity controls to the vulnerable code. The processor adds simple instrumentation that only changes the application's behavior when unauthorized data tampering occurs while preserving the application's normal behavior. When certain operations may cause unauthorized data tampering, the processor takes proper measures to stop the operations. The processor translates the intermediate representation back to a machine code and replaces the original binary with the machine code.

Abstract: Disclosed herein are embodiments of systems, methods, and products providing real-time anti-malware detection and protection. The computer uses artificial intelligence techniques to learn and detect new exploits in real time and protect the full system from harm. The computer trains a first machine learning model for executable files. The computer trains a second machine learning model for non-executable files. The computer trains a third machine learning model for network traffic. The computer identifies malware using the various machine learning models. The computer restores to a clean, uncorrupted state using virtual machine technology. The computer reports the detected malware to a security server, such as security information and even management (SIEM) systems, by transmitting detection alert message regarding the malware. The computer interacts with an administrative system over an isolated control network to allow the system administrator to correct the corruption caused by the malware.

Abstract: A method for safe and efficient use of airport runway capacity includes receiving, at an air traffic control system at an airport, airport data related to movement areas of the airport, time data related to a time period, aircraft data related to a plurality of aircraft expected to operate into and out of the airport during the time period, and environmental data related to environmental conditions predicted for the airport during the time period. The method further includes computing a probability distribution for inter-aircraft spacing by applying the airport data, the time data, the aircraft data, and the environmental data to a trained Bayesian network, producing the probability distribution for the inter-aircraft spacing as an output observation of the trained Bayesian network, and, using the probability distribution and a confidence value, identifying an inter-aircraft spacing value for the plurality of aircraft expected to operate into and out of the airport during the time period.

Abstract: A method for adaptively providing processed data to elements of a distributed network, includes a processor partitioning data from a plurality of data sources, including big data from a plurality of big data sources based on defined needs of the elements; the processor storing the partitioned data in a central data source and a subset of the partitioned data in one or more cache memories in proximity to the elements; receiving a data request from a network element; determining a time-sensitivity of data responsive to the data request; supplying a response to the data request for non-time-sensitive data; and supplying the response to the data request for time-sensitive data.

Abstract: Disclosed herein are embodiments of a cloud data synchronization system enabling an user operating a mobile client device to download mission-specific data sets from a fixed cloud-based server system to a database of the mobile client device, and then use the downloaded data sets independently on the mobile client device when the mobile client device is disconnected from a network connecting to the fixed cloud-based server system. When connectivity to the fixed cloud-based server system is re-established by the mobile client device in an intermittent and bandwidth-limited communication network environment, the fixed cloud-based server system may provide bi-directional data synchronization between records of the fixed cloud-based server system and the mobile client device to update the data sets on the fixed cloud-based server system and the mobile client device while operating in the intermittent and bandwidth-limited communication network environment.

Abstract: A system, apparatus and method for light diffusion and testing fixtures. The system includes remote derangement controls to test the operation of a battery backup system associated with a fixture. The light fixture may incorporate light diffusion features including back mounted light sources, channeled corners in a translucent material and/or pitted surfaces of a translucent material. The system may further include remote monitoring elements and/or sensors to evaluate proper operation of the light diffusion characteristics of a fixture during operation of the battery backup system.

Abstract: Disclosed herein are embodiments of systems, methods, and products comprising a computing device, which provides Efficient Data-In-Transit Protection Techniques for Handheld Devices (EDITH) to protect data-in-transit. An end user device (EUD) may generate a multicast data packet. The EDITH module of the EUD encapsulates the data packet in a GRE packet and directs the GRE packet to a unicast destination address of an EDITH Multicast Router included in an infrastructure. The EDITH module on the EUD double compresses and double encrypts the GRE packet. The EDITH module on the infrastructure decrypts and decompresses the double compressed and double encrypted GRE packet to recreate the GRE packet. The EDITH module on the infrastructure decapsulates the GRE packet to derive the original multicast data packet, and distributes the original multicast data packet to the multiple group member based on the multicast destination address included in the original multicast data packet.

Abstract: In a network, a common agnostic data exchange method between two devices native to the network, the devices using different formats and transmission protocols, includes invoking a proxy at each device, and a first proxy receiving a first data record from a first device, the first data record having a first format. The first proxy identifies the first format by comparing a first pattern of the first data record to reference patterns of one or more reference data records and determines if a sufficient pattern match exists between the first pattern and the reference pattern. The first proxy translates the first data record's format into an inter-proxy data record having an inter-proxy format and transmits the inter-proxy data record to a second proxy coupled to a second device. The second proxy translates the inter-proxy data record to a second data record having a format employed at the second device.

Abstract: A real-time recommendation system includes a non-transitory, computer-readable storage medium having encoded thereon instructions that a processor executes to receive data from data sources that includes one or more data records. The processor then identifies features in data of a data record, extracts and buffers the features, and applies the features to a feature detect mechanism. The feature detect mechanism includes feature detect algorithm and more recommender algorithms that are encapsulated in a feature detection object. The feature detection object may be a Strategy/Composite feature detection object that includes Strategy design patterns. The processor further executes to reject a feature in response to failures of the feature to match at least one of the Strategy design patterns, and in real time, select and install features that match one or more of the Strategy design patterns into one or more recommender algorithms.

Abstract: Disclosed herein are embodiments of a network monitoring device for a supercomputer system having a plurality of supercomputer nodes. The network monitoring device may utilize plug-in software modules to provide network monitoring capabilities related to discovering the network topologies of the supercomputer system, determining network and computing resources that are available for new applications in the supercomputer system, collecting network and computing resources that are being used by running software applications in the supercomputer system, and monitoring running software applications on the supercomputer system.

Abstract: In a network, a common agnostic data exchange method between two devices native to the network, the devices using different formats and transmission protocols, includes invoking a proxy at each device, and a first proxy receiving a first data record from a first device, the first data record having a first format. The first proxy identifies the first format by comparing a first pattern of the first data record to reference patterns of one or more reference data records and determines if a sufficient pattern match exists between the first pattern and the reference pattern. The first proxy translates the first data record's format into an inter-proxy data record having an inter-proxy format and transmits the inter-proxy data record to a second proxy coupled to a second device. The second proxy translates the inter-proxy data record to a second data record having a format employed at the second device.

Abstract: Disclosed herein are embodiments of systems, methods, and apparatus that execute classification techniques to enable high-quality analysis of ingest data by interpreting and categorizing disparate data points of the ingest data. The execution of the classification techniques leads to isolation of intrinsic properties of each data point to represent the essence of what the overall ingest data indicates. The classification techniques further enables classification of the ingest data, which is unencumbered by any ingest data format changes, such as ordering of data components, encoding, or properties associated with the ingest data that are likely to change without altering meaning conveyed by the ingest data.

Abstract: Disclosed herein are embodiments of systems and methods that dynamically reconfigure a multi-tiered system of network devices and software applications in response to an ongoing and/or anticipated cyber-attack. The dynamic reconfiguration of the network devices may consist of a wide range of processes, which may include generating new network addresses for individual network devices; reconfiguring the network devices by creating firewalls, changing protocols between the network devices in a multi-tier reconfiguration solution, changing the cloud infrastructure provider of the network devices, even when the underlying network infrastructure ecosystem differs across cloud service providers (CSPs); and maintaining a secure and updated data model of a record of reconfigured network devices and their dependencies to allow legitimate users of the network devices to understand reconfiguration actions that are hidden from malicious users such as hackers and cyber-attackers.

Abstract: A sign assembly such as an exit sign can be mounted on either a wall or a ceiling of a structure. The sign assembly includes a housing with a frame that supports a square lens. The frame has one wall section that is removable to enable the lens to be removed and reinserted in a different orientation relative to the frame. As a result, the lens can be oriented properly when the sign housing is turned to be mounted on either the wall or the ceiling. The lens is free of electrical contacts and electrical terminals.

Abstract: A real-time recommender method includes receiving streaming data records; applying tokenizer objects to a received data record to identify, extract and buffer data elements. The method applies the buffered data elements to a feature detect tree that includes a root node and one or more subsequent branch nodes, a set of the subsequent branch nodes defining a path culminating in a leaf node, by applying a data element to the root node and testing the data element to reject or select the data element, applying a prior-selected data element to subsequent branch nodes, and conducting at each of the subsequent branch nodes, a test to reject or select the prior-selected data element, and stopping, for a selected path, the applying and testing after the prior-selected data element reaches a path's leaf node. The method still further includes installing each data element reaching the path's leaf node, as a feature, into one or more recommender algorithm models.

Abstract: A computer-implemented method for migrating a monolithic legacy software system to a well-defined modular target software architecture includes selecting a method, based on predefined patterns, for transforming the software legacy software system; creating an abstract syntax tree from the legacy software system's source code; from the abstract syntax tree, determining a flow of the source code and any coding violations and coding smells in the legacy software system's source code; using the flow and the coding violations, identifying architecture issues in the legacy software system; scheduling tasks for transforming the legacy software system into the target software architecture; automatically generating new source code according to the target software architecture; and automatically and autonomously refactoring the new source code.

Abstract: A method for improving efficiency of a training program begins with a processor monitoring and adapting execution of a training exercise of the training program. The processor determines a training program effectiveness measure including determining trainee skill improvement demonstrated during the training exercise, and monitoring and determining correctness and timeliness of trainee actions during the training exercise. The processor then determines a training program cost measure by determining a first monetary cost for the execution of the at least one training exercise, determining a second monetary cost associated with trainee manhours for the training exercise, and generating the training program cost measure based on the first and second monetary costs. The processor then computes a ratio of the training program effectiveness measure to the training program cost measure.